Existing approaches to measuring intersectional discrimination (i.e., racial/ethnic-, sexual orientation, and/or gender-related) and related cardiometabolic health behaviors (CHB; i.e., physical inactivity, dysregulated sleep, and tobacco and alcohol use) lack the ability to capture the real-world context in which intersectional discrimination occurs, the momentary appraisal of such events, and resultant behaviors.

This 4-year, NIH funded study (1R01HL169503-01A1) will use a validated novel geographically-explicit momentary assessment (GEMA) method which allows for the accurate capturing of the duration and frequency of exposure situated within the context in which these behaviors and exposures occur among young sexual and gender minorities (YSGM) as well as explore risk and protective factors for harmful CHB among diverse YSGM. Further, this study will demonstrate the utility of the predictive models and variable creation for future CHB Just in Time interventions.